Log-mel spectrograms are of size \(80{\times }21\)  – the network takes a decision for a frame given its context: \(\pm \) 10ms, 21 frames in total. Activation functions are ELUs [1]} for all deep learning models and these are optimized with stochastic gradient descent (batch size: 64), using ADAM [2]} and early stopping – when validation loss (categorical cross-entropy) does not decrease after 10 epochs.
